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115
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AIPS
2006
15 years 5 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
125
Voted
NAR
2006
98views more  NAR 2006»
15 years 3 months ago
oGNM: online computation of structural dynamics using the Gaussian Network Model
An assessment of the equilibrium dynamics of biomolecular systems, and in particular their most cooperativefluctuationsaccessibleundernativestate conditions, is a first step towar...
Lee-Wei Yang, A. J. Rader, Xiong Liu, Christopher ...
132
Voted
ICPR
2010
IEEE
15 years 10 months ago
Probabilistic Modeling of Dynamic Traffic Flow across Non-Overlapping Camera Views
In this paper, we propose a probabilistic method to model the dynamic traffic flow across nonoverlapping camera views. By assuming the transition time of object movement follows a...
Ching-Chun Huang, Wei-Chen Chiu, Sheng-Jyh Wang, J...
143
Voted
ICMCS
2008
IEEE
118views Multimedia» more  ICMCS 2008»
15 years 10 months ago
A stochastic model of selective visual attention with a dynamic Bayesian network
Recent studies in signal detection theory suggest that the human responses to the stimuli on a visual display are nondeterministic. People may attend to different locations on the...
Derek Pang, Akisato Kimura, Tatsuto Takeuchi, Junj...
134
Voted
IEEEIAS
2008
IEEE
15 years 10 months ago
Dynamic Substitution Model
In this paper, we present the Dynamic Injection Model (DIM) and its variant the Static Injection Model (SIM). DIM is a model that allows any iterative block cipher to accept a var...
Mohamed Abo El-Fotouh, Klaus Diepold